We analyze the segmentation produced by our model with a variety of metrics. To ensure our segments contain pixels which center patches that are similar to each other, we calculate several measures of similarity and compare these values for pixels in the same segment to pixels in a different segment. We capture different notions of similarity, from structural and textural image-specific metrics to a more general distance-based metric: the previously discussed SSIM, as well as the Relative Dimensionless Global Error (ERGAS), and the root mean squared error (RMSE) [1]}, [2]}, [3]}.
